Health Language Blog

Health information exchange (HIE) is a critical component to the future of healthcare. As more systems are created to improve patient outcomes and improve operational efficiencies, it will become increasingly important for various health data systems to be able to communicate with one another.

More payments are being tied to successful reporting on a number of fronts like Meaningful Use and the Physician Quality Reporting System, and practices and payers will have to make sure the data in their HIT systems is clean to to be paid.

Unfortunately, payers and providers have acquired a variety of systems over the years that use different terminologies. This makes it hard for these systems to communicate with each other and even harder for healthcare providers to develop a comprehensive view of billing and patient data.

This is where data normalization comes in to play. Data normalization allows for apples-to-apples comparisons of information from different systems by 1) standardizing local content to terminology standards and 2) semantically translating data between standards to eliminate any ambiguity of meaning.

In general, data normalization establishes a foundation for achieving semantic interoperability and creates an infrastructure that enables data sharing and aggregation. From meeting the interoperability and terminology requirements of the Meaningful Use initiative to ensuring the clinical data in which an ACO is built upon is complete and semantically understood, data normalization is critical to healthcare.

A well-designed data normalization solution can ensure better visibility into operations, quality measures and other criteria simply not feasible with disparate systems which do not share a single source of terminology truth.

What are some of the biggest data normalization challenges you’ve faced? Share your answers in the comments.

About the Author

Brian Diaz is the Director of Integrated Solutions with Health Language, part of Wolters Kluwer Health. When not working, Brian is soaking up the Colorado experience with his family but still cheers on the Golden Gophers.

Bob Schmidt

A common data modeling tool, ERwin and its DBA culture is the biggest obstacle to normalization. ERwin is licensed on a per-user basis and is apparently seen as expensive as all the shops I've been in purchase very few licenses. The DBA culture encourages this. They are the only ones with access to ERwin. The DBA culture jealously guards their exclusive access to the tool.
The result is that regardless of how beautiful the data modeling product is, it is not accessible to the BAs and QAs and developers and other non-DBAs.
ERwin is not inter-operable with other tools or services. Say one is doing a conversion project, or the ETL of a data warehouse. The services of those projects cannot interface with ERwin to facilitate both faster and more accurate processes.

McLain Causey

Thanks for your note, Bob.
Fortunately, we offer more inclusive enterprise licensing models than per-seat, usage-based, or concurrency-based models. This is because we want everyone who needs to be involved in the process to have the access they require—we don’t feel that our customers benefit from licensing policies or software design that restricts access, and we view enterprise terminology management as a “team sport.” So your enterprise can have wider access to modeling and other tooling through easy-to-use Web-based applications requiring no installation. Additionally, we work closely with our customers to ensure that modeling terminologies doesn’t require a DBA background—we abstract that complexity behind intuitive graphical models, while also allowing low-level access as needed.
Further, while Erwin has a couple customers in the healthcare domain, Health Language lives and breathes healthcare on both the clinical and administrative sides of the industry. We have hundreds of healthcare standards built in to the Language Engine and those are maintained by a large team of medical informaticists and terminologists. Additionally, we offer value-added content that goes above and beyond what’s available from the standards bodies, such as enhanced GEMS (SmartGEMS) and proprietary mappings between various terminologies, as well as the ability to easily extend and subset standard terminologies to meet your use cases. So, in a nutshell, we make your job easier and ensure that you always have the most up-to-date healthcare standards to work with.
Finally, for organizations lacking the expertise or staffing to tackle certain terminology challenges, we offer everything from best practices and training to robust outsource services by a large team of clinicians and terminologists with years of expertise.